Objective This study addresses the adaptive automatic berthing control problem for underactuated vessels, considering both internal/external uncertainties and false data injection (FDI) attacks. The objective is to develop a control strategy that efficiently utilizes network resources while ensuring robustness against cyber-attacks.

Methods First, an equivalent motion model for underactuated vessels under FDI attacks is established using differential homeomorphism transformation, addressing design challenges posed by the vessels' underactuated nature. Second, on the basis of the idea of event-triggered control (ETC), an event-triggered sampling mechanism (ESM) is introduced in the sensor-controller (S-C) channel. This mechanism uses berthing position and velocity errors as trigger conditions to sample dynamic vessel data, thereby reducing network communication load and mitigating the impact of FDI attacks on the closed-loop system. Third, a new error transformation based on prescribed performance control (PPC) is introduced to enhance berthing accuracy and stability by addressing yaw angle and velocity constraints. Additionally, radial basis function (RBF) neural networks combined with single-parameter learning methods are employed to represent dynamic uncertainties and unknown time-varying disturbances in a linear parameterized form, simplifying engineering calculations. Within the backstepping framework, an adaptive neural network controller is designed, and its stability is evaluated using Lyapunov theory. Finally, simulations are conducted in Simulink to validate the proposed control algorithm.

Results The proposed control scheme ensures stable convergence of the vessel's attitude and velocity to zero, with sampling times ranging from 69 to 347. The results demonstrate that the influence of attack signals on control performance is significantly reduced, confirming the scheme's effectiveness in reducing communication load and resisting FDI attacks.

Conclusions The proposed strategy is simple, robust, and precise, with strong applicability in practical engineering scenarios. It provides a new approach for the automatic berthing control of underactuated vessels in networked environments.